FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2936486224> ?p ?o ?g. }

• W2936486224 endingPage "184" @default.
• W2936486224 startingPage "170" @default.
• W2936486224 abstract "Fine scale maps of soil properties enable efficient land management and inform earth system models. Recent efforts to create soil property maps from field observations tend to use similar tree-based machine learning interpolation approaches, but often deal with depth of predictions, validation, and uncertainty differently. One of the main differences in approaches is whether to model individual depths of interest separately as ‘2D’ models, or to create models that incorporate depth as a predictor variable creating a ‘3D’ model that can make predictions for all depths. It is unclear how choice of 2D or 3D approach influences model accuracy and uncertainty due to lack of direct comparison and inconsistent presentation of results in past studies. This study compares 2D and 3D methods for mapping soil electrical conductivity (salinity), pH, sum of fine and very fine sands, and organic carbon at 30 m resolution for the upper 432,000 km2 of the Colorado River Watershed of the United States of America. A new, simple, model-agnostic relative prediction interval (RPI) approach to report uncertainty is presented that scales prediction interval width to the 95% interquantile width of the original training sample distribution. The RPI approach enables direct comparison of uncertainty between properties and depths and is easily interpretable by end users. Results indicate that 3D mapping of soil properties with strong variation with depth can result in substantial areas with much higher uncertainty that coincide with unrealistic predictions relative to 2D models, even though 3D models had slightly better global cross-validation scores. Maps and global model summaries of RPI proved helpful in identifying these issues with 3D models. These results suggest that the use of RPI or similar approaches to evaluate models can identify accuracy problems not evident in global validation diagnostics." @default.
• W2936486224 created "2019-04-25" @default.
• W2936486224 creator A5062420200 @default.
• W2936486224 creator A5077450089 @default.
• W2936486224 date "2019-08-01" @default.
• W2936486224 modified "2023-09-26" @default.
• W2936486224 title "Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data" @default.
• W2936486224 cites W1221070779 @default.
• W2936486224 cites W1509048661 @default.
• W2936486224 cites W1891744174 @default.
• W2936486224 cites W1930678412 @default.
• W2936486224 cites W1973517598 @default.
• W2936486224 cites W1981646498 @default.
• W2936486224 cites W1983108390 @default.
• W2936486224 cites W1990096846 @default.
• W2936486224 cites W2019894796 @default.
• W2936486224 cites W2023312901 @default.
• W2936486224 cites W2039660802 @default.
• W2936486224 cites W2040049981 @default.
• W2936486224 cites W2049842380 @default.
• W2936486224 cites W2050179592 @default.
• W2936486224 cites W2052681112 @default.
• W2936486224 cites W2054325787 @default.
• W2936486224 cites W2055336003 @default.
• W2936486224 cites W2057223139 @default.
• W2936486224 cites W2066626803 @default.
• W2936486224 cites W2067728464 @default.
• W2936486224 cites W2072682706 @default.
• W2936486224 cites W2119534769 @default.
• W2936486224 cites W2129961764 @default.
• W2936486224 cites W2130560194 @default.
• W2936486224 cites W2157919513 @default.
• W2936486224 cites W2191676425 @default.
• W2936486224 cites W2498963908 @default.
• W2936486224 cites W2528492999 @default.
• W2936486224 cites W2567438935 @default.
• W2936486224 cites W2567805992 @default.
• W2936486224 cites W2588003345 @default.
• W2936486224 cites W2613126452 @default.
• W2936486224 cites W2615937871 @default.
• W2936486224 cites W2725897987 @default.
• W2936486224 cites W2782582361 @default.
• W2936486224 cites W2803913164 @default.
• W2936486224 cites W2809196510 @default.
• W2936486224 cites W2911964244 @default.
• W2936486224 cites W4212883601 @default.
• W2936486224 cites W92141931 @default.
• W2936486224 doi "https://doi.org/10.1016/j.geoderma.2019.03.037" @default.
• W2936486224 hasPublicationYear "2019" @default.
• W2936486224 type Work @default.
• W2936486224 sameAs 2936486224 @default.
• W2936486224 citedByCount "20" @default.
• W2936486224 countsByYear W29364862242019 @default.
• W2936486224 countsByYear W29364862242020 @default.
• W2936486224 countsByYear W29364862242021 @default.
• W2936486224 countsByYear W29364862242022 @default.
• W2936486224 countsByYear W29364862242023 @default.
• W2936486224 crossrefType "journal-article" @default.
• W2936486224 hasAuthorship W2936486224A5062420200 @default.
• W2936486224 hasAuthorship W2936486224A5077450089 @default.
• W2936486224 hasBestOaLocation W29364862241 @default.
• W2936486224 hasConcept C104471815 @default.
• W2936486224 hasConcept C114614502 @default.
• W2936486224 hasConcept C115961682 @default.
• W2936486224 hasConcept C119857082 @default.
• W2936486224 hasConcept C137800194 @default.
• W2936486224 hasConcept C150547873 @default.
• W2936486224 hasConcept C154945302 @default.
• W2936486224 hasConcept C159390177 @default.
• W2936486224 hasConcept C159750122 @default.
• W2936486224 hasConcept C205649164 @default.
• W2936486224 hasConcept C2778067643 @default.
• W2936486224 hasConcept C2778755073 @default.
• W2936486224 hasConcept C32230216 @default.
• W2936486224 hasConcept C33923547 @default.
• W2936486224 hasConcept C39432304 @default.
• W2936486224 hasConcept C41008148 @default.
• W2936486224 hasConcept C58640448 @default.
• W2936486224 hasConcept C71864017 @default.
• W2936486224 hasConceptScore W2936486224C104471815 @default.
• W2936486224 hasConceptScore W2936486224C114614502 @default.
• W2936486224 hasConceptScore W2936486224C115961682 @default.
• W2936486224 hasConceptScore W2936486224C119857082 @default.
• W2936486224 hasConceptScore W2936486224C137800194 @default.
• W2936486224 hasConceptScore W2936486224C150547873 @default.
• W2936486224 hasConceptScore W2936486224C154945302 @default.
• W2936486224 hasConceptScore W2936486224C159390177 @default.
• W2936486224 hasConceptScore W2936486224C159750122 @default.
• W2936486224 hasConceptScore W2936486224C205649164 @default.
• W2936486224 hasConceptScore W2936486224C2778067643 @default.
• W2936486224 hasConceptScore W2936486224C2778755073 @default.
• W2936486224 hasConceptScore W2936486224C32230216 @default.
• W2936486224 hasConceptScore W2936486224C33923547 @default.
• W2936486224 hasConceptScore W2936486224C39432304 @default.
• W2936486224 hasConceptScore W2936486224C41008148 @default.
• W2936486224 hasConceptScore W2936486224C58640448 @default.
• W2936486224 hasConceptScore W2936486224C71864017 @default.
• W2936486224 hasLocation W29364862241 @default.

• next